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Carbon nanodots in cancer theranostics: Bridging nanostructure design and biomedical applications

Year: 2026
Type: article
Abstract: Carbon nanodots (CNDs) are ultra-small (2–10 nm) zero-dimensional carbon nanoparticles that exhibit remarkable nanoscale-dependent properties. Their size-dependent photoluminescence facilitates sensitive detection and real-time bioimaging, and their abundant surface functional groups allow for modification by a variety of chemical techniques for targeted drug delivery and controlled therapeutic release. Collectively, these inherent structural and optical characteristics demonstrate exciting potential for CNDs to function as dual-use nanoprobes for diagnostic and therapeutic purposes. CNDs can be prepared using a variety of top-down approaches (e.g., chemical oxidation and laser ablation) and bottom-up approaches (e.g., hydrothermal and microwave-assisted) for synthesis. Bottom-up approaches are preferred for nanodots to afford greater control over the size of the nanoparticles and features of the surface/chemical state of the nanoparticles. Each synthesis route requires careful characterization using a variety of methods (e.g., photoluminescence spectroscopy, FTIR, UV–visible spectroscopy, and TEM) to confirm nanoscale morphology, surface chemistry, and optical behavior needed for anticipated biomedical uses. CNDs have a range of potential biomedical applications, including bioimaging, biosensing, drug delivery, and antioxidant therapy. In cancer theranostics, surface-engineered CNDs have shown the ability to improve tumor-specific accumulation, provide greater therapeutic selectivity, and enhance photodynamic therapy using reactive oxygen species (ROS) generated in a more controllable manner. These properties have synergistic effects because ongoing innovations in terms of engineering CNDs and integrating the functional CNDs in preclinical and clinical applications are positioning CNDs as next-generational nanoplatforms for combined diagnosis and therapy, as well as precision oncology.
Language: English
Open Access status: gold
Estimated APC paid: $1,280
Award: G750875753
OpenAlex ID: W7170605274
FWCI:
Cites: 144
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